Osteopontin promotes host defense during<i>Klebsiella pneumoniae</i>-induced pneumonia
Bibliographic record
Abstract
Klebsiella pneumoniae is a common cause of nosocomial pneumonia. Osteopontin (OPN) is a phosphorylated glycoprotein involved in inflammatory processes, some of which is mediated by CD44. The aim of this study was to determine the role of OPN during K. pneumoniae-induced pneumonia. Wild-type (WT) and OPN knockout (KO) mice were intranasally infected with 10⁴ colony forming units of K. pneumoniae, or administered Klebsiella lipopolysaccharides (LPS). In addition, recombinant OPN (rOPN) was intranasally administered to WT and CD44 KO mice. During Klebsiella pneumonia, WT mice displayed elevated pulmonary and plasma OPN levels. OPN KO and WT mice showed similar pulmonary bacterial loads 6 h after infection; thereafter, Klebsiella loads were higher in lungs of OPN KO mice and the mortality rate in this group was higher than in WT mice. Early neutrophil recruitment into the bronchoalveolar space was impaired in the absence of OPN after intrapulmonary delivery of either Klebsiella bacteria or Klebsiella LPS. Moreover, rOPN induced neutrophil migration into the bronchoalveolar space, independent from CD44. In vitro, OPN did not affect K. pneumoniae growth or neutrophil function. In conclusion, OPN levels were rapidly increased in the bronchoalveolar space during K. pneumoniae pneumonia, where OPN serves a chemotactic function towards neutrophils, thereby facilitating an effective innate immune response.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".